{"as_of":"2026-08-18T07:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6e5c8aebc3a4c82ab57783a62bd8586ad2c1cb7f5d9d5880f95aed96dfdcc2ca","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T04:15:47.272214Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.10317/citation-record","integrity":"/paper/2608.10317/integrity","json":"/paper/2608.10317/citation-record.json","paper":"/paper/2608.10317"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2606.02800","last_updated":"2026-06-23T17:33:32Z","snapshot_observed_at":"2026-07-06T23:43:07.940839Z","submitted_at":"2026-06-01T19:12:30Z","title":"Cosmos 3: Omnimodal World Models for Physical AI","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.02800","snapshot_observed_at":"2026-08-14T04:15:47.104194Z","title":"Cosmos 3: Omnimodal world models for physical ai.arXiv preprint arXiv:2606.02800, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.104194Z"},"links":{"cited_paper":"/paper/2606.02800","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:ae379b2272d6e41e20f1619c04994512925353d66d34ce944e367949d28e5e54","observation_id":"3f305a91-9c03-4d30-b6b0-afa92c927691","resolution":{"observed_at":"2026-08-14T04:15:47.104194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:48.136522Z","title":"AI City Challenge 2026 Track 3: Anomalous events in transportation","venue":null,"work_id":"1668bd33-a177-4680-a2be-a2e62af01fae","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.114999Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:6ba2c70096e913eb711ac34b6e68553e57ece46bdad553bb6520356be4dd9e48","observation_id":"46df54f8-1f3f-4f47-bdcb-a078af73548c","resolution":{"observed_at":"2026-08-14T04:15:48.153764Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:48.087487Z","title":"Anastasiu","venue":null,"work_id":"e29d2801-681b-4798-a537-46c41dea9be5","year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.121597Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:a055e22fb76125635c6311b1e522434961cf50594c0dcbf0d7ef2934d7953c5d","observation_id":"a0105357-abb8-448d-86c8-cc20be7cc976","resolution":{"observed_at":"2026-08-14T04:15:48.105112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:48.053598Z","title":"Highway traffic videos dataset.https://www.kaggle.com/datasets/aryashah2k/highw ay-traffic-videos-dataset, 2023","venue":null,"work_id":"5a637079-056e-4540-888d-f8d02455d4bf","year":2023},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.124877Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:eee84a704e342dd14a75b165713a855a38f4d3d90aadb57f287e3143d77ef2bd","observation_id":"a0eee666-5b56-4df7-a6ea-d5266dc4d806","resolution":{"observed_at":"2026-08-14T04:15:48.077135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:48.028085Z","title":"SO-TAD: A surveillance-oriented benchmark for traffic accident detection.Neurocomputing, 618:129061, 2025","venue":null,"work_id":"68d6f4f1-6d19-4a76-a5f9-aab2ba273fa0","year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.128937Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:0d9ecb6c7078f37ad939b150b2c856038f312c15707b534ee41b40cc3c955ed5","observation_id":"19607163-f9ca-46b9-8136-fd8a588a21d9","resolution":{"observed_at":"2026-08-14T04:15:48.045673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:48.007035Z","title":"CARLA: An open urban driving simulator","venue":null,"work_id":"e7f50833-fe89-479a-92f4-434a22bca5be","year":2017},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.133194Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:d6207d888d67d2563e432f7ee442650f3d31c45ef84306714bf944bb9e2ae334","observation_id":"2c0ed578-9b58-4c12-9c48-1b0f4dd07421","resolution":{"observed_at":"2026-08-14T04:15:48.013693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.983839Z","title":"VLMEvalKit: An open-source toolkit for evaluating large multi-modality models","venue":null,"work_id":"4ed68383-7532-4780-8485-fdfcb8b05db5","year":null},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.141253Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:078a9a1f0270e4fbcd997234328657ce657b8648400702da1da0487df45a22d0","observation_id":"67180ab7-bf62-4e42-912c-f3f3db5ebfe2","resolution":{"observed_at":"2026-08-14T04:15:47.988008Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.960866Z","title":"FishEye8K: A benchmark and dataset for fisheye camera object detection","venue":null,"work_id":"53a1c660-1842-4924-ac1d-4b629f067ddc","year":2023},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.146927Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:09e0fb51a04d8747bb4bc82e003998d524513947e7c92abd16c8f2765a7e763b","observation_id":"bb96a017-6b06-4e0a-9a1f-4b075ffb664d","resolution":{"observed_at":"2026-08-14T04:15:47.974333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.950202Z","title":"FETV: Fisheye traffic violation dataset.https://gith ub.com/MoyoG/FETV, 2026","venue":null,"work_id":"e8c9843c-0631-4e57-b752-e584351ac9c8","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.150722Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:809f5ce44dd3324dc1a428bc951ea650017a52b19c9f9668ff92d5b0dd4ebd9b","observation_id":"ca93e09c-06b5-4e1f-b691-10cbeb74f5a6","resolution":{"observed_at":"2026-08-14T04:15:47.954141Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.925017Z","title":"Gemini 3 model documentation.https://ai.google.dev/gemini-api/docs/mode ls, 2026","venue":null,"work_id":"9d862488-527d-44d6-8f06-5a6a6940b611","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.154680Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:27f88987c589af786233e1f399b15515fb50dbeef6eb0a20cce2a2ffe2df67b3","observation_id":"b7160441-17ed-4107-b197-0c0ac3fa8f64","resolution":{"observed_at":"2026-08-14T04:15:47.937479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.911302Z","title":"Gemma 4 model card.https://ai.google.dev/gemma/docs/core/model_card_4,","venue":null,"work_id":"de209cd9-64f2-45c0-a932-e6a7e379621f","year":null},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.159708Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:6e22a31a3bf322423b8b635d40aa7da0ff46de43e318b64311fb4507eeee9718","observation_id":"7b3cd486-3f5a-4f99-8aee-93f4b822c78c","resolution":{"observed_at":"2026-08-14T04:15:47.916038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.165955Z","title":"AccidentBench: Benchmarkingmultimodal understanding and reasoning in vehicle accidents and beyond.arXiv preprint arXiv:2509.26636, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.165955Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:844aeba1975e5cff7589a4efa48ea9af3fa18d2539a5909965138fd2c58fa01d","observation_id":"9cb6663f-7dad-4c5a-ba7d-82fbf81a3b4b","resolution":{"observed_at":"2026-08-14T04:15:47.165955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.19877","last_updated":"2025-05-26T12:05:16Z","snapshot_observed_at":"2026-08-10T09:10:24.017088Z","submitted_at":"2025-05-26T12:05:16Z","title":"Vad-R1: Towards Video Anomaly Reasoning via Perception-to-Cognition Chain-of-Thought","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.19877","snapshot_observed_at":"2026-08-14T04:15:47.172052Z","title":"Vad- R1: Towards video anomaly reasoning via perception-to-cognition chain-of-thought.arXiv preprint arXiv:2505.19877, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.172052Z"},"links":{"cited_paper":"/paper/2505.19877","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:a79fffdc55e87217c219842b5cbc6c57b15a2fa826aaf1a011bcd47b41c9ac84","observation_id":"e5c0632f-ce6a-42b3-a323-029901b15531","resolution":{"observed_at":"2026-08-14T04:15:47.172052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.899018Z","title":"Psi: A benchmark for human interpretation and response in traffic interactions","venue":null,"work_id":"9c584b7e-d803-4cb0-8c7a-3ea302c7cd8e","year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.175595Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:d0ab2dfa6accd96d96c06004922378bafc15e3c531e375ef4e21a1cc5ea8bfbe","observation_id":"e0598c95-0c69-4d0c-ab36-a62db5c1ccfe","resolution":{"observed_at":"2026-08-14T04:15:47.902994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.886281Z","title":"Gonzalez, Hao Zhang, and Ion Stoica","venue":null,"work_id":"a1e6bec7-7c85-442a-bcdf-a68598d5fdc5","year":2023},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.183018Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:d1d0bf12dc6423c1937f3b2ddbf1770a32d006d05d4c4bf1c360210df8e45e41","observation_id":"d0026e25-f9ae-4c37-a2f9-7cd6d47a2744","resolution":{"observed_at":"2026-08-14T04:15:47.890000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.873814Z","title":"Abnormal event detection at 150 FPS in MATLAB","venue":null,"work_id":"2009bcee-896e-4b02-bbe4-1803d679b134","year":2013},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.187439Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:a0a771d1ddfa49959bf5c588d2d795d764765976d3dd9e3c53db6c6b17e14f2c","observation_id":"95e21ce9-52c5-4282-9ca7-9a2716e33e8c","resolution":{"observed_at":"2026-08-14T04:15:47.877145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.862843Z","title":"A revisit of sparse coding based anomaly detection in stacked RNN framework","venue":null,"work_id":"1091f4ed-0c85-4307-96ee-30d48f057b1b","year":2017},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.190585Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:f3741d7fb3d36ed4acc64b182cd50e2f1851b981c3950435fb30dada0bea8d7e","observation_id":"9109de84-3e80-42fc-8793-207cd5cbbba0","resolution":{"observed_at":"2026-08-14T04:15:47.866475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.851324Z","title":"Localizing anomalies from weakly-labeled videos.IEEE Transactions on Image Processing, 2021","venue":null,"work_id":"8ff84ceb-4f07-4d13-a51f-ddd141449cbb","year":2021},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.196087Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:ea52d36c133fd1a0c6a1a10b28449e145e5a4fe4c33fcb8cd7cd52bb8aa4f594","observation_id":"4973e3f6-f4a2-4cbc-8955-be2b8028e485","resolution":{"observed_at":"2026-08-14T04:15:47.855097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.839412Z","title":"Cosmos-Reason2-8B.https://huggingface.co/nvidia/Cosmos-Reason2-8B, 2026","venue":null,"work_id":"a77ed5e4-3460-47af-8805-5bc778705d29","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.199199Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:2c598867a44bf7b9335575a52ec7795c4154884eda9189dc669efa6f394d03dd","observation_id":"b0125766-3323-40d8-969f-63a3ed67dab7","resolution":{"observed_at":"2026-08-14T04:15:47.843894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.827818Z","title":"Cosmos-Reason2-32B.https://huggingface.co/nvidia/Cosmos-Reason2-32B, 2026","venue":null,"work_id":"925c14a0-60ba-42aa-8771-834016b8f154","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.202101Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:9ec4a13ae259d85b1460ce9d8b1f7921103a4b6ba3ace801976d690c096c97cc","observation_id":"1ab4ba88-d488-498c-843d-0f4e7ca6492d","resolution":{"observed_at":"2026-08-14T04:15:47.832293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.21631","last_updated":"2025-11-27T12:16:54Z","snapshot_observed_at":"2026-08-17T13:26:10.378579Z","submitted_at":"2025-11-26T17:59:08Z","title":"Qwen3-VL Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.21631","snapshot_observed_at":"2026-08-14T04:15:47.207899Z","title":"Qwen3-VL technical report.arXiv preprint arXiv:2511.21631, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.207899Z"},"links":{"cited_paper":"/paper/2511.21631","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:a66c59b5fb9dde404659207e9a490c3bba2281c5f2f5ac63a5f6b97b3b88cc3b","observation_id":"76d0f12b-6743-4caa-834a-bae9e9c66599","resolution":{"observed_at":"2026-08-14T04:15:47.207899Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.05782","last_updated":"2018-11-16T06:28:36Z","snapshot_observed_at":"2026-08-14T18:27:58.023723Z","submitted_at":"2018-09-16T00:01:39Z","title":"CADP: A Novel Dataset for CCTV Traffic Camera based Accident Analysis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.05782","snapshot_observed_at":"2026-08-14T04:15:47.211271Z","title":"Shah, Jean-Baptiste Lamare, Tuan Nguyen-Anh, and Alexander Hauptmann","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.211271Z"},"links":{"cited_paper":"/paper/1809.05782","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:b9e960e5c94befc1e4e5af7ed3d1350cec43b7b9d5b3ee99bc115e5b25834f3d","observation_id":"ddd12107-b068-4064-9562-dea836b9f40a","resolution":{"observed_at":"2026-08-14T04:15:47.211271Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.796867Z","title":"Real-world anomaly detection in surveillance videos","venue":null,"work_id":"4f682fe4-ae23-4e67-97a4-569991377b07","year":null},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.214482Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:9f4d01edd9e0b7f06b4ed8eed1d4bf8541d802900d3b0bf2b83e3606f3099cbe","observation_id":"a7c51e93-2c27-426c-8da0-1c82f846fcdc","resolution":{"observed_at":"2026-08-14T04:15:47.812172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.13564","last_updated":"2025-08-19T06:55:06Z","snapshot_observed_at":"2026-08-05T18:59:34.703300Z","submitted_at":"2025-08-19T06:55:06Z","title":"The 9th AI City Challenge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.13564","snapshot_observed_at":"2026-08-14T04:15:47.227259Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.227259Z"},"links":{"cited_paper":"/paper/2508.13564","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:e578d0b15be91de978ec88bed9b876f0b24fbdd94c44526e92d20c51889d5a0d","observation_id":"29d4a380-1a16-4a98-8429-5a086a1e3ddd","resolution":{"observed_at":"2026-08-14T04:15:47.227259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.770665Z","title":"Anastasiu, Ming-Ching Chang, et al","venue":null,"work_id":"3492d6b4-050e-4995-8cde-297db06b0618","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.231261Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:8c7b16ae5d5382f133268b79b313a6b7a2c597ab88a497b0893b2be01d382c7a","observation_id":"0e70a6cb-1483-43f7-bfac-b2c1f57d95ba","resolution":{"observed_at":"2026-08-14T04:15:47.786303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.737817Z","title":"PSI VQA: Egocentric dashcam pedestrian intent benchmark.https: //huggingface.co/datasets/ise-ice-lab/PSI_VQA, 2026","venue":null,"work_id":"5eac580d-f26d-41b2-9889-4e7662f33123","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.239707Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:6a5220d56e0988deeb8b1941b6acdddad439f0642bba983e19df18b5e4f457e5","observation_id":"b1eb4264-f346-4ac1-8a19-ac8e722e5a14","resolution":{"observed_at":"2026-08-14T04:15:47.746524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.12386","last_updated":"2022-09-26T03:00:50Z","snapshot_observed_at":"2026-08-16T16:29:59.395310Z","submitted_at":"2022-09-26T03:00:50Z","title":"TAD: A Large-Scale Benchmark for Traffic Accidents Detection from Video Surveillance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.12386","snapshot_observed_at":"2026-08-14T04:15:47.246832Z","title":"TAD: A large-scale benchmark for traffic accidents detection from video surveillance.arXiv preprint arXiv:2209.12386, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.246832Z"},"links":{"cited_paper":"/paper/2209.12386","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:d7ab122e727e8afe46d44a94a3bcc3d3428061aa44b1813f7a38eb603e8ca57d","observation_id":"0d58a557-4257-4d84-ae0e-e17e82258ec9","resolution":{"observed_at":"2026-08-14T04:15:47.246832Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.21917","last_updated":"2026-07-08T19:55:21Z","snapshot_observed_at":"2026-08-13T17:46:01.346846Z","submitted_at":"2026-05-21T02:44:27Z","title":"MAVEN: A Multi-stage Agentic Annotation Pipeline for Video Reasoning Tasks","version":2},"cited_work":{"arxiv_id":"2605.21917","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.21917","snapshot_observed_at":"2026-08-14T04:15:47.456554Z","title":"MAVEN: A Multi-stage Agentic Annotation Pipeline for Video Reasoning Tasks","venue":"cs.CV","work_id":"01f5bea6-beea-439f-bbe2-d930b5132a7f","year":2026},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.250064Z"},"links":{"cited_paper":"/paper/2605.21917","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:c177685370475773ba7b85966e3a9604b1b69393ead9eaaac0f926fa1c756783","observation_id":"74b155b7-5c33-4547-adeb-4fb2bee29e03","resolution":{"observed_at":"2026-08-14T04:15:47.462383Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12235","last_updated":"2024-06-29T08:15:27Z","snapshot_observed_at":"2026-08-16T13:42:00.312543Z","submitted_at":"2024-06-18T03:19:24Z","title":"Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.12235","snapshot_observed_at":"2026-08-14T04:15:47.253229Z","title":"Holmes-VAD: Towards unbiased and explainable video anomaly detection via multi-modal LLM.arXiv preprint arXiv:2406.12235, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.253229Z"},"links":{"cited_paper":"/paper/2406.12235","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:bb810c60ae43370adeb3b7373cbd66a50fa861e3d3ed810c32ccc840bc98a2e1","observation_id":"4b2e36d7-45e2-4c00-9aa2-41f68505c0da","resolution":{"observed_at":"2026-08-14T04:15:47.253229Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.06171","last_updated":"2025-03-14T10:23:06Z","snapshot_observed_at":"2026-08-17T13:28:50.254490Z","submitted_at":"2024-12-09T03:05:34Z","title":"Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.06171","snapshot_observed_at":"2026-08-14T04:15:47.256267Z","title":"Holmes-VAU: Towards long-term video anomaly understanding at any granularity","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.256267Z"},"links":{"cited_paper":"/paper/2412.06171","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:cfe86066efe32ffaee517eb62f9794ea97dc993f3d2dd1b2ea49e248c37c40ff","observation_id":"7da42dbe-9420-490d-a2ce-107ef5c6bd0f","resolution":{"observed_at":"2026-08-14T04:15:47.256267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.664655Z","title":"Weinberger, and Yoav Artzi","venue":null,"work_id":"51db4ae2-da74-4949-a4b7-407aa6523224","year":2020},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.259641Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:8c1f170d3a9151351c6457392d94abeac548686a231d1ce353a60ebbdd6eeef8","observation_id":"65607504-42fc-4b49-9cd0-099f662ac296","resolution":{"observed_at":"2026-08-14T04:15:47.684838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.12589","last_updated":"2025-05-19T00:57:04Z","snapshot_observed_at":"2026-08-18T02:06:36.869670Z","submitted_at":"2025-05-19T00:57:04Z","title":"SurveillanceVQA-589K: A Benchmark for Comprehensive Surveillance Video-Language Understanding with Large Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.12589","snapshot_observed_at":"2026-08-14T04:15:47.263691Z","title":"SurveillanceVQA-589K: A benchmark for comprehensive surveillance video-language understanding with large models.arXiv preprint arXiv:2505.12589, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.263691Z"},"links":{"cited_paper":"/paper/2505.12589","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:d4f3230d0d80e5fd2817d5953329bf37ae36da8eedd36fd4926d61987b6288f3","observation_id":"149f5536-42ec-4d19-9965-3ea8ab966e7b","resolution":{"observed_at":"2026-08-14T04:15:47.263691Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.13925","last_updated":"2023-12-04T13:34:01Z","snapshot_observed_at":"2026-08-16T14:57:57.446225Z","submitted_at":"2023-09-25T07:46:56Z","title":"Towards Surveillance Video-and-Language Understanding: New Dataset, Baselines, and Challenges","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.13925","snapshot_observed_at":"2026-08-14T04:15:47.267925Z","title":"Towards surveillance video-and-language understanding: New dataset, baselines, and challenges.arXiv preprint arXiv:2309.13925, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.267925Z"},"links":{"cited_paper":"/paper/2309.13925","citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:662f2281fbfd14eee48910dada5007539259bc3dd8812250a7a3bd76adcd16e2","observation_id":"b63a9a90-af0d-49d7-a8d7-41bb00a5c18d","resolution":{"observed_at":"2026-08-14T04:15:47.267925Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T04:15:47.643836Z","title":"Barbados traffic analysis challenge.https://zindi.africa/competitions/barbados-traffic -analysis-challenge/data, 2023","venue":null,"work_id":"67017fd9-e172-46d3-a619-087c4f039fe1","year":2023},"citing_paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T04:15:47.272214Z"},"links":{"citing_paper":"/paper/2608.10317"},"observation_digest":"sha256:7889f8c105b93324130482894a106834245a28ab0ca54015df2854b7561ea580","observation_id":"717f9f20-0bf7-4de7-a629-78ea67155af9","resolution":{"observed_at":"2026-08-14T04:15:47.647982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2608.10317","last_updated":"2026-08-10T23:40:07Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T14:02:51.209394Z","submitted_at":"2026-08-10T23:40:07Z","title":"From Detection to Understanding: TAR and TAR-Bench for Multi-Task Traffic Anomaly Reasoning"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":1,"verified_fuzzy":22},"total_outbound_references":34},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2608.10317."}